Three-Stage Data-Driven Phase Analysis to Reveal Generator-Site Origin Source of Forced Oscillations Under Resonance
Bibliographic record
Abstract
This paper proposes a novel three-stage near real-time phase-driven procedure to locate the generator-type source of forced oscillations, inspired by the concept of Transient Energy Function (TEF), independent of the amplitude of any signal. In the commencement of the process, each generation bus is assigned with its active power and angular velocity angles reached from the reduced power system graph. Next, the difference in the synchronous generators’ active power angles and the difference in their angular velocity angles is exploited as the graph branches’ weight coefficients. Then, three exclusive and first-proposed decision functions are applied sequentially. First, the weighting coefficients of branches and nodes are fed to the first decision function. Regardless of the grid size, the result of this step is limited to up to four generators. The next step focuses exclusively on the first step outcomes, which results in two generators as recommended items. The last step, relying on the output of the second one, reveals the target generator accurately. The methodological procedure has been validated on the New England 10-machine 39-bus benchmark power system modelled in the Real-Time Digital Simulator (RTDS/RSCAD) and then scrutinised in the MATLAB environment. In each study scenario, the results are compared with the conventional transient energy method. The simulation results revealed that the presented approach reliably releases all sources, including limit cycle and turbine governing reference signal modulation, under the most intense parametric resonance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".